CN105140940A - Method for determining capacity of energy storage device integrated with independent new energy system - Google Patents

Abstract

The invention is a method for determining the capacity of an independent new energy system connected to an energy storage device, which can be applied to scientific research and engineering applications in new energy related fields. In the present invention, based on the wind power data, based on the discrete Fourier transform theory and the concept of signal energy, an energy storage optimization configuration method for an independent new energy system is proposed, which can optimize the energy storage configuration of an independent wind storage system and an optical storage system . The invention can quickly and accurately configure the capacity of energy storage according to user needs, so as to meet the needs of actual engineering energy storage design.

Description

A method for determining the capacity of an independent new energy system connected to an energy storage device

technical field

The invention relates to a method for determining the capacity of an independent new energy system connected to an energy storage device, and belongs to the technical field of new energy power generation.

Background technique

At present, the large-scale application of new energy power generation has occupied a certain proportion in the domestic and foreign power supply, which has played a positive and effective role in energy conservation, emission reduction, and development of clean energy. In the utilization of new energy power generation, because wind power and photovoltaic power generation are affected by meteorological factors, they have intermittent and random fluctuations, resulting in output power fluctuations, which have a non-negligible negative impact on the grid and loads. Scholars at home and abroad stabilize the power fluctuations of renewable energy power generation affected by meteorological factors by designing energy storage devices.

Energy storage technology is an important means to achieve energy balance and ensure the normal operation of the power grid, and has an irreplaceable support and optimization role. However, because the capacity of the energy storage configuration is configured according to the maximum, and the investment cost is high, it is not economical. Therefore, considering the economy of investment cost and the effectiveness of function realization, a reasonable capacity allocation is very necessary for energy storage applications. In actual engineering, the selection of energy storage capacity is usually realized based on experience, so it is difficult to guarantee the accuracy of the energy storage capacity. Therefore, it is necessary to rely on the characteristics of local wind and wind, rely on algorithms to quickly and accurately determine the energy storage capacity, and effectively improve the output characteristics of wind and wind power.

Contents of the invention

Purpose of the invention: This invention proposes a method for determining the capacity of an independent new energy system connected to an energy storage device, which can be applied to the technical field of new energy power generation.

Technical solution: In order to achieve the above purpose, the present invention adopts the following technical solution: a method for determining the capacity of an independent new energy system connected to an energy storage device, including the following steps:

1) Discrete Fourier transform is performed on the acquired power data to obtain the amplitude-frequency curve;

2) Spectrum analysis is performed on the power data, the DC component is eliminated, and the inverse discrete Fourier transform is performed to obtain the power data that eliminates the DC component, that is, the reference data;

3) Assume specific frequency and specific power data;

4) Introduce the concept of signal energy and calculate the ratio of energy to reference energy;

5) The energy storage capacity is obtained by calculating the configuration time and energy storage power.

As optimization, in step 1), the amplitude-frequency result formula after Fourier transform:

$\left\{\begin{array}{c}\mathrm{<span\; class="notranslate">\; S</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; f</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; P</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>{<span\; class="notranslate">\; \&lsqb;</span>}^{\mathrm{<span\; class="notranslate">\; S</span>}}\\ \mathrm{<span\; class="notranslate">\; f</span>}<span\; class="notranslate">\; =</span>{<span\; class="notranslate">\; \&lsqb;</span>\mathrm{<span\; class="notranslate">\; f</span>}<span\; class="notranslate">\; \&lsqb;</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; \&rsqb;</span><span\; class="notranslate">\; ,</span><span\; class="notranslate">\; ...</span><span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; f</span>}<span\; class="notranslate">\; \&lsqb;</span>\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; \&rsqb;</span><span\; class="notranslate">\; ,</span><span\; class="notranslate">\; ...</span><span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; f</span>}<span\; class="notranslate">\; \&lsqb;</span>\mathrm{<span\; class="notranslate">\; N</span>}<span\; class="notranslate">\; \&rsqb;</span><span\; class="notranslate">\; \&rsqb;</span>}^{\mathrm{<span\; class="notranslate">\; T</span>}}\end{array}\right.<span\; class="notranslate">\; ;</span>$

In the formula: N is the number of sampling points; P is the power data, P=[P[1],...,P[i],...,P[N]] ^T ; F(P) is the power data Liye transform; S[i] is the magnitude of the i-th f[i], S[i]=R[i]+jI[i], R[i] and I[i] are the real part and imaginary part respectively Department; f is the sampling frequency, f[i]=f·(i-1)/N.

As an optimization, in step 2), the formula for eliminating the DC component is:

${\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}<span\; class="notranslate">\; \&lsqb;</span>\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; \&rsqb;</span><span\; class="notranslate">\; =</span>\left\{\begin{array}{cc}\mathrm{<span\; class="notranslate">\; 0</span>}<span\; class="notranslate">\; +</span>\mathrm{<span\; class="notranslate">\; j</span>}\mathrm{<span\; class="notranslate">\; 0</span>}& {\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 0</span>}\\ \mathrm{<span\; class="notranslate">\; S</span>}<span\; class="notranslate">\; \&lsqb;</span>\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; \&rsqb;</span>& {\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; \&NotEqual;</span>\mathrm{<span\; class="notranslate">\; 0</span>}\end{array}\right.<span\; class="notranslate">\; ;</span>$

The power data (reference data) P ₀ formula for eliminating the DC component is:

P ₀ =F ^-1 (S ₀ )=[P ₀ [1],...,P ₀ [i],...,P ₀ [N]] ^T ;

In the formula, F ^-1 (S ₀ ) is the discrete Fourier transform of S ₀ ; P ₀ [i] is the power data (reference data) that eliminates the DC component, the data at the i-th sampling point.

As optimization, in step 3), assuming a specific frequency f (T=1/f), then a group of specific power data P ₁ formula is:

${\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; \&lsqb;</span>\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; \&rsqb;</span><span\; class="notranslate">\; =</span>\left\{\begin{array}{cc}\mathrm{<span\; class="notranslate">\; 0</span>}<span\; class="notranslate">\; +</span>\mathrm{<span\; class="notranslate">\; j</span>}\mathrm{<span\; class="notranslate">\; 0</span>}& {\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; <</span>\mathrm{<span\; class="notranslate">\; 0</span>}\\ {\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}<span\; class="notranslate">\; \&lsqb;</span>\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; \&rsqb;</span>& {\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; \&Greater\; Equal;</span>\mathrm{<span\; class="notranslate">\; 0</span>}\end{array}\right.<span\; class="notranslate">\; ;</span>$

P ₁ =F ^-1 (S ₁ )=[P ₁ [1],...,P ₁ [i],...,P ₁ [N]] ^T ;

In the formula, F ^-1 (S ₀ ) is the discrete Fourier transform of S ₁ ; P ₁ [i] is the specific power data, the data at the i-th sampling point; the period interval of the specific power data P ₁ for 0-T.

As an optimization, in step 4), the signal energy is defined as follows:

$\mathrm{<span\; class="notranslate">\; E.</span>}<span\; class="notranslate">\; =</span>\sqrt{\underset{\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{\mathrm{<span\; class="notranslate">\; N</span>}}{<span\; class="notranslate">\; \&Sigma;</span>}}\mathrm{<span\; class="notranslate">\; x</span>}{<span\; class="notranslate">\; \&lsqb;</span>\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; \&rsqb;</span>}^{\mathrm{<span\; class="notranslate">\; 2</span>}}}<span\; class="notranslate">\; ;</span>$

In the formula, E is the energy of the signal; x[i] is the power data of the i-th sampling point;

The formula for calculating the ratio of energy E ₁ to reference energy E ₀ is as follows:

η=E ₁ /E ₀ .

As an optimization, in step 5), the average value of the original power data is set as the energy storage power, and the energy storage capacity is obtained by configuring time and energy storage power.

Technical effect: Compared with the prior art, the present invention adopts the method for determining the capacity of the independent new energy system connected to the energy storage device proposed by the present invention, which can quickly and accurately establish the capacity of the energy storage device and effectively improve the power output characteristics of the new energy electric field , to better play the role of new energy power generation in the power system is of great significance to the economy of new energy electric fields and its active power regulation ability.

Description of drawings

Fig. 1 is the annual data of wind power generation power in a certain area;

Figure 2 is the data of wind power generation power in a certain area in January;

Fig. 3 is the amplitude-frequency characteristic curve of wind power generation power data in a certain area;

Fig. 4 is the wind power generation power data (reference data) that eliminates DC component;

FIG. 5 is a specific flow for determining configuration time.

specific implementation plan

Below in conjunction with accompanying drawing, the technical process of invention is described in detail:

In order to illustrate the principle of the present invention, the present invention selects the wind power data of a certain area as the research object. Figure 1 and Figure 2 show the wind power data of a certain region for the whole year and January, respectively. It can be seen from Figure 1 and Figure 2 that the annual average of wind power is 9.5976kW, and the maximum power reaches 335kW; the fluctuation of wind power is quite large. This phenomenon is caused by the climatic conditions and wind characteristics of an area.

1) Discrete Fourier transform (DFT) is performed on the acquired power data to obtain the amplitude-frequency curve. The magnitude-frequency result (frequency domain) after DFT is given in the following formula:

$\left\{\begin{array}{c}\mathrm{<span\; class="notranslate">\; S</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; f</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; P</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>{<span\; class="notranslate">\; \&lsqb;</span>}^{\mathrm{<span\; class="notranslate">\; S</span>}}\\ \mathrm{<span\; class="notranslate">\; f</span>}<span\; class="notranslate">\; =</span>{<span\; class="notranslate">\; \&lsqb;</span>\mathrm{<span\; class="notranslate">\; f</span>}<span\; class="notranslate">\; \&lsqb;</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; \&rsqb;</span><span\; class="notranslate">\; ,</span><span\; class="notranslate">\; ...</span><span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; f</span>}<span\; class="notranslate">\; \&lsqb;</span>\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; \&rsqb;</span><span\; class="notranslate">\; ,</span><span\; class="notranslate">\; ...</span><span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; f</span>}<span\; class="notranslate">\; \&lsqb;</span>\mathrm{<span\; class="notranslate">\; N</span>}<span\; class="notranslate">\; \&rsqb;</span><span\; class="notranslate">\; \&rsqb;</span>}^{\mathrm{<span\; class="notranslate">\; T</span>}}\end{array}\right.<span\; class="notranslate">\; ;</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; )</span>$

In the formula: N - the number of sampling points;

P——power data, P=[P[1],...,P[i],...,P[N]] ^T ;

F(P)——DFT the power data;

S[i]——the amplitude of the i-th f[i], S[i]=R[i]+jI[i], R[i] and I[i] are real and imaginary parts respectively;

f——sampling frequency, f[i]=f·(i-1)/N. ;

Spectrum analysis is carried out to the wind power generation data (annual year) in a certain area in Fig. 1, and the corresponding amplitude-frequency characteristics are obtained. The specific curve is shown in Fig. 3. When f=0 (DC component), its amplitude is 9.5976. In the wind power, the magnitude of the frequency greater than 2×10 ^-4 Hz is close to zero.

2) Spectrum analysis is performed on the power data, the DC component is eliminated, and the inverse discrete Fourier transform (IDFT) is performed to obtain the power data (reference data) with the DC component eliminated. After spectrum analysis of the power data, the DC component (frequency is 0) is the joint output of the wind power generation and energy storage system, which is the ideal output target of the whole system. When determining the configuration time, the direct component does not need to be considered, so in the second step, the DC component is eliminated first. Specifically, it can be calculated by formula (2):

${\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}<span\; class="notranslate">\; \&lsqb;</span>\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; \&rsqb;</span><span\; class="notranslate">\; =</span>\left\{\begin{array}{cc}\mathrm{<span\; class="notranslate">\; 0</span>}<span\; class="notranslate">\; +</span>\mathrm{<span\; class="notranslate">\; j</span>}\mathrm{<span\; class="notranslate">\; 0</span>}& {\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 0</span>}\\ \mathrm{<span\; class="notranslate">\; S</span>}<span\; class="notranslate">\; \&lsqb;</span>\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; \&rsqb;</span>& {\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; \&NotEqual;</span>\mathrm{<span\; class="notranslate">\; 0</span>}\end{array}\right.<span\; class="notranslate">\; ;</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 2</span>}<span\; class="notranslate">\; )</span>$

Inverse discrete Fourier transform (IDFT) is performed on S ₀ to obtain power data (reference data) P ₀ that eliminates the DC component. Here P ₀ is the benchmark data, which is one of the important parameters in the energy storage configuration process.

P ₀ =F ^-1 (S ₀ )=[P ₀ [1],...,P ₀ [i],...,P ₀ [N]] ^T ; (3)

Among them, F ^-1 (S ₀ )——perform IDFT on S ₀ ;

P ₀ [i]——power data (reference data) that eliminates the DC component, the data at the i-th sampling point.

The data curve of wind power generation that eliminates the DC component means that Figures 1 and 2 are moved down by 9.5976kW as a whole, and the baseline of the vertical axis becomes -9.5976kW. Figure 4 is the benchmark data for calculating the power-energy ratio of wind power generation.

3) Assuming specific frequency and specific power data. Based on S ₀ and ,P ₀ in the second step, assuming a specific frequency f (T=1/f), a set of specific power data P ₁ can be calculated by formula (4) and formula (5).

${\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; \&lsqb;</span>\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; \&rsqb;</span><span\; class="notranslate">\; =</span>\left\{\begin{array}{cc}\mathrm{<span\; class="notranslate">\; 0</span>}<span\; class="notranslate">\; +</span>\mathrm{<span\; class="notranslate">\; j</span>}\mathrm{<span\; class="notranslate">\; 0</span>}& {\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; <</span>\mathrm{<span\; class="notranslate">\; 0</span>}\\ {\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}<span\; class="notranslate">\; \&lsqb;</span>\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; \&rsqb;</span>& {\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; \&Greater\; Equal;</span>\mathrm{<span\; class="notranslate">\; 0</span>}\end{array}\right.<span\; class="notranslate">\; ;</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 4</span>}<span\; class="notranslate">\; )</span>$

P ₁ =F ^-1 (S ₁ )=[P ₁ [1],...,P ₁ [i],...,P ₁ [N]] ^T ; (5)

In the formula, F ^-1 (S ₀ )——do IDFT on S ₁ ;

P ₁ [i]——Specific power data, the data at the i-th sampling point; the period interval of specific power data P ₁ is 0-T.

4) The concept of signal energy is introduced to calculate the ratio of energy to reference energy. The concept of signal energy is introduced in the present invention, and its specific definition is as follows:

$\mathrm{<span\; class="notranslate">\; E.</span>}<span\; class="notranslate">\; =</span>\sqrt{\underset{\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{\mathrm{<span\; class="notranslate">\; N</span>}}{<span\; class="notranslate">\; \&Sigma;</span>}}\mathrm{<span\; class="notranslate">\; x</span>}{<span\; class="notranslate">\; \&lsqb;</span>\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; \&rsqb;</span>}^{\mathrm{<span\; class="notranslate">\; 2</span>}}}<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 6</span>}<span\; class="notranslate">\; )</span>$

In the formula, E——the energy of the signal, in the present invention, the signal is power data (comprising the power data (reference data) and specific power data of eliminating DC component);

x[i]——the power data of the i-th sampling point.

The energies of the power data P ₀ and P ₁ are respectively E ₀ and E ₁ , which can be calculated by formula (6). In addition, E ₀ of the power data (reference data) P ₀ from which the DC component has been eliminated is the reference energy.

The formula for calculating the ratio of energy E ₁ to reference energy E ₀ is as follows:

η=E ₁ /E ₀ ; (7)

The specific process is as follows:

a) set the energy ratio η ₀ ;

b) Based on all the frequency values of S ₀ in the second step, the specific frequency gradually takes values from low frequency (f _min ) to high frequency (f _max ), and new specific power data is generated using equations (4) and (5) P1 _;

C) by formula (6) and formula (7), calculate the energy ratio η of energy E ₁ and reference energy;

d) When the energy ratio η reaches the set value, the program stops and returns to a specific frequency (final) value f, and its corresponding period T is the configuration time. In the program, when η-η ₀ <=0.005, it is considered that the energy ratio η has reached the set value; η-η ₀ <=0.005 is the criterion for the end of the loop in the program.

The specific process is shown in Figure 5.

In the process of determining the configuration time, the energy ratio η ₀ directly affects the configuration time, and indirectly affects the capacity of the configured energy storage and the economy of the independent wind storage system. Therefore, it is very important to set the energy ratio η ₀ . For an independent new energy system, the proportion of important loads and the location of energy storage in the independent system should be fully considered, and an appropriate energy ratio η ₀ should be set to obtain a practical configuration time.

In the present invention, it is assumed that the energy ratio η ₀ =90%, and the allocation time allocation of wind power generation is studied.

5) The average value of the original power data is set as the energy storage power P, then the energy storage capacity is obtained by configuring the time and energy storage power, that is, P*T.

The average wind power generation power in a certain area is 9.5976kW, so the energy storage power of the configured wind storage system is 9.5976kW.

According to different energy ratios η ₀ , Table 1 shows the corresponding energy storage configuration of independent wind storage systems in a certain area. In Table 1, when 90% of the energy of wind power generation (reference data) is guaranteed, the configuration time is 63.0216h, which is relatively long and economical; and when 80%, 70% and 60% of the reference energy are guaranteed, The configuration time is reduced to 30.9541h, 20.0458h, and 13.2929h respectively. In these three cases, the power supply reliability of important loads during failure is improved, and the economy of the entire system is also guaranteed. In summary, for an independent wind storage system, it can be configured based on the economy and reliability of the wind storage system; in order to ensure higher reliability, the energy storage configuration power is 9.5976kW, and the capacity is 297.0851kWh; in order to balance the economy , the energy storage configuration power is 9.5976kW, and the capacity is 127.5799kWh.

Table 1 Energy storage configuration of wind power generation in a region (different energy ratios)

Claims (6)

1. determine a method for independent new energy resources system access capacity of energy storing device, it is characterized in that: comprise the following steps:

1) discrete Fourier transform is carried out to the power data obtained, obtain amplitude frequency curve;

2) spectrum analysis is carried out to power data, eliminate DC component, carry out inverse discrete Fourier transform and change, obtain the power data eliminating DC component, i.e. reference data;

3) characteristic frequency and specific power data is supposed;

4) introduce the concept of signal energy, calculate the ratio of energy and reference energy;

5) stored energy capacitance is obtained by setup time and energy storage power calculation.

2. the method determining independent new energy resources system access capacity of energy storing device according to claim 1, is characterized in that: in step 1) in, the amplitude-frequency result formula after Fourier transform:

$\left\{\begin{array}{c}S=F\left(P\right)={\&lsqb;}^S\\ f={\&lsqb;f\&lsqb;1\&rsqb;,...,f\&lsqb;i\&rsqb;,...,f\&lsqb;N\&rsqb;\&rsqb;}^T\end{array}\right.;$

In formula: N is the number of sampled point; P is power data, P=[P [1] ..., P [i] ..., P [N]] ^t; F (P) is for carry out Fourier transform to power data; S [i] is the amplitude of i-th f [i], and S [i]=R [i]+jI [i], R [i] and I [i] is respectively real part and imaginary part; F is sample frequency, f [i]=f (i-1)/N.

3. the method determining independent new energy resources system access capacity of energy storing device according to claim 1, is characterized in that: in step 2) in, the formula eliminating DC component is:

$S_0\&lsqb;i\&rsqb;=\left\{\begin{array}{cc}0+j0& f_i=0\\ S\&lsqb;i\&rsqb;& f_i\&NotEqual;0\end{array}\right.;$

Eliminate power data (reference data) P of DC component ₀formula is:

P ₀＝F ^-1(S ₀)＝[P ₀[1],...,P ₀[i],....,P ₀[N]] ^T；

In formula, F ^-1(S ₀) be to S ₀carry out discrete Fourier transform; P ₀[i] is the power data (reference data) of elimination DC component, in the data of i-th sampled point.

4. the method determining independent new energy resources system access capacity of energy storing device according to claim 1, is characterized in that: in step 3) in, suppose a characteristic frequency f (T=1/f), then one group of specific power data P ₁formula is:

$S_1\&lsqb;i\&rsqb;=\left\{\begin{array}{cc}0+j0& f_i<0\\ S_0\&lsqb;i\&rsqb;& f_i\&GreaterEqual;0\end{array}\right.;$

P ₁＝F ^-1(S ₁)＝[P ₁[1],...,P ₁[i],....,P ₁[N]] ^T；

In formula, F ^-1(S ₀) be to S ₁carry out discrete Fourier transform; P ₁[i] is specific power data, in the data of i-th sampled point; Specific power data P ₁periodic region between be 0-T.

5. the method determining independent new energy resources system access capacity of energy storing device according to claim 1, is characterized in that: in step 4) in, signal energy is defined as follows:

$E=\sqrt{\underset{i=1}{\overset{N}{\&Sigma;}}x{\&lsqb;i\&rsqb;}^2};$

In formula, E is the energy of signal; X [i] is the power data of i-th sampled point;

ENERGY E ₁with reference energy E ₀the computing formula of ratio is as follows:

η＝E ₁/E ₀。

6. the method determining independent new energy resources system access capacity of energy storing device according to claim 1, it is characterized in that: in step 5) in, the mean value of original power data is set as energy storage power, obtains stored energy capacitance by setup time and energy storage power.